Counting on count data models

Rainer Winkelmann

IZA World of Labor, 2015, No 148, 148

Abstract: Often, economic policies are directed toward outcomes that are measured as counts. Examples of economic variables that use a basic counting scale are number of children as an indicator of fertility, number of doctor visits as an indicator of health care demand, and number of days absent from work as an indicator of employee shirking. Several econometric methods are available for analyzing such data, including the Poisson and negative binomial models. They can provide useful insights that cannot be obtained from standard linear regression models. Estimation and interpretation are illustrated in two empirical examples.

Keywords: Poisson regression; negative binomial distribution; zero-inflation; hurdle model (search for similar items in EconPapers)
JEL-codes: C2 C25 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://wol.iza.org/articles/counting-on-count-data-models-1.pdf (application/pdf)
http://wol.iza.org/articles/counting-on-count-data-models (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iza:izawol:journl:y:2015:n:148

Access Statistics for this article

IZA World of Labor is currently edited by Pierre Cahuc

More articles in IZA World of Labor from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Institute of Labor Economics (IZA) ().